Breast imaging for breast cancer screening and diagnostic work-up follows a multi-modality approach, including X-ray mammography and tomosynthesis, ultrasound, and Magnetic Resonance (MR) imaging. In order to completely characterize a lesion, it is essential for the radiologist to track individual lesions across multiple imaging studies and to structure the report on the level of individual lesions. In current practice, the radiologist has to visually identify corresponding lesions across imaging studies, since the patient positioning differs significantly between the different modalities, e.g., two projection images in X-ray mammography with a strongly compressed breast versus a three-dimensional Magnetic Resonance image of a freely hanging breast or an ultrasound image showing only part of the breast under examination.
Currently reports are made on an individual basis per imaging study, without linking to a generic reference frame. Consequently, when combining information from multiple reports, corresponding lesions need to be identified by the reader, which can be a challenging task. When reviewing a follow-up examination of a known lesion, the lesion needs to be searched and found “from scratch” which is time-consuming and, especially for the less experienced user, error-prone.
WO 2011/052515 A1 discloses an information processing apparatus for deforming an original image includes an obtaining unit configured to obtain a deformation rule by associating a movement of a feature area caused by deformation of the original image with the deformation, and a deformation unit configured to deform the original image in accordance with the deformation rule, using, as a condition of constraint, position information about a feature area of the target image and a corresponding area of the original image.
US 2005/0096515 A1 discloses a patient surface image therapy includes the steps of acquiring a three-dimensional reference image of an area to be treated, acquiring a three-dimensional treatment image of the area to be treated; matching the reference image to the treatment image; and calculating any differences between the reference image and the treatment images to generate patient repositioning parameters.